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Bayesian Nonparametric Causal Inference for High-Dimensional Nutritional Data via Factor-Based Exposure Mapping
Dafne Zorzetto, Zizhao Xie, Julian Stamp +2
Diet plays a crucial role in health, and understanding the causal effects of dietary patterns is essential for informing public health policy and personalized nutrition strategies.…
A Bayesian framework for cost-effectiveness analysis with time-varying treatment decisions
Esteban Fernández-Morales, Emily M. Ko, Nandita Mitra +2
Cost-effectiveness analyses (CEAs) compare the costs and health outcomes of treatment regimes to inform medical decisions. With observational claims data, CEAs must address nonrand…
Considerations for Estimating Causal Effects of Informatively Timed Treatments
Arman Oganisian
Epidemiological studies are often concerned with estimating causal effects of a sequence of treatment decisions on survival outcomes. In many settings, treatment decisions do not o…
Bayesian Sensitivity Analyses for Policy Evaluation with Difference-in-Differences under Violations of Parallel Trends
Seong Woo Han, Nandita Mitra, Gary Hettinger +1
Violations of the parallel trends assumption pose significant challenges for causal inference in difference-in-differences (DiD) studies, especially in policy evaluations where pre…
Untangling Sample and Population Level Estimands in Bayesian Causal Computation
Arman Oganisian
Model-based Bayesian inference for sample and population-level causal estimands has been growing in popularity. This literature routinely emphasizes clear specification of the targ…
Bayesian shrinkage priors for penalized synthetic control estimators in the presence of spillovers
Esteban Fernández-Morales, Arman Oganisian, Youjin Lee
Synthetic control (SC) methods are widely used to estimate the effects of policy interventions, especially those targeting specific geographic regions, referred to as units. These…